{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# opencv transforms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from opencv_transforms import transforms"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "image = np.random.random((1024,1024,3))*255"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(2048, 2048, 3)\n",
      "CPU times: user 28.1 ms, sys: 35.9 ms, total: 64 ms\n",
      "Wall time: 61.9 ms\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "resize = transforms.Resize(size=(2048, 2048))\n",
    "image = resize(image)\n",
    "print(image.shape)"
   ]
  }
 ],
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   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
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